Bayesian Reasoning and Machine Learning

Machine Learning is the study of data-driven methods capable of mimicking, understanding and aiding
human and biological information processing tasks. In this pursuit, many related issues arise such as how
to compress data, interpret and process it. Often these methods are not necessarily directed to mimicking
directly human processing but rather to enhance it, such as in predicting the stock market or retrieving
information rapidly. In this probability theory is key since inevitably our limited data and understanding
of the problem forces us to address uncertainty. In the broadest sense, Machine Learning and related fields
aim to ‘learn something useful’ about the environment within which the agent operates. Machine Learning
is also closely allied with Artificial Intelligence, with Machine Learning placing more emphasis on using data
to drive and adapt the model.

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